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Polymarket Macro Asymmetric Longshot Trader

v0.0.2

Systematically finds markets with huge asymmetric payoff -- markets priced at 2-10% where cross-category macro analysis suggests the REAL probability is 15-3...

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Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for diagnostikon/polymarket-macro-asymmetric-longshot-trader.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Polymarket Macro Asymmetric Longshot Trader" (diagnostikon/polymarket-macro-asymmetric-longshot-trader) from ClawHub.
Skill page: https://clawhub.ai/diagnostikon/polymarket-macro-asymmetric-longshot-trader
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

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openclaw skills install polymarket-macro-asymmetric-longshot-trader

ClawHub CLI

Package manager switcher

npx clawhub@latest install polymarket-macro-asymmetric-longshot-trader
Security Scan
Capability signals
CryptoCan make purchasesRequires sensitive credentials
These labels describe what authority the skill may exercise. They are separate from suspicious or malicious moderation verdicts.
VirusTotalVirusTotal
Benign
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OpenClawOpenClaw
Suspicious
high confidence
!
Purpose & Capability
The skill claims (in the top-level summary) that no env vars or credentials are required and is described as 'instruction-only' in the registry metadata, but clawhub.json declares a required env var SIMMER_API_KEY and a pip dependency simmer-sdk, and a runnable trader.py is included. Requiring an API key and an SDK is coherent with a trading bot, but it is inconsistent with the earlier 'no credentials / instruction-only' claim.
Instruction Scope
SKILL.md and trader.py describe discovering markets, scoring them, and executing trades via a SimmerClient. The instructions and code focus on market data and trading operations and do not attempt to read unrelated filesystem locations or unknown network endpoints. The code's default behavior is paper trading unless explicitly run with a live flag.
Install Mechanism
There is no formal install spec, but clawhub.json lists a pip dependency 'simmer-sdk'. Installing a pip package is normal for this purpose (moderate risk). There are no direct downloads from personal URLs or archive extraction. The install footprint is limited to a standard pip package, which is expected for a runtime SDK but should be reviewed (verify simmer-sdk origin and review its code).
!
Credentials
The skill requires SIMMER_API_KEY (declared in clawhub.json and used in trader.py) even though the registry metadata earlier said 'Required env vars: none' — that's a significant mismatch. Multiple SIMMER_* tunables are exposed to control risk parameters; these are reasonable for a trading bot, but SIMMER_API_KEY grants the ability to place (real) trades if used with live=True. Ensure the key's permissions are limited and you understand the distinction between paper and live modes.
Persistence & Privilege
always is false and autostart is false in clawhub.json, which limits forced persistence. The skill includes an automaton entrypoint (trader.py) and is flagged managed=true; that means the platform can run it as an automaton, but by default it should not autostart. The agent is allowed to invoke the skill autonomously (platform default) — combined with a valid SIMMER_API_KEY and a user action to enable 'live', this could place real trades. This combination is notable but not itself proof of maliciousness.
What to consider before installing
This skill is a trading bot and is largely coherent with that purpose, but there are clear inconsistencies in the metadata you should resolve before installing. Key actions to consider: - Treat SIMMER_API_KEY as sensitive: the code uses it to construct a SimmerClient and can place real trades if run with live=True. Only provide an API key with the minimum required permissions and preferably a test/paper key. - Confirm the owner and source: the package claims 'Diagnostikon' but has no homepage; verify the simmer-sdk package origin and review its code before installation. - Expect pip installation of simmer-sdk (moderate risk). Inspect that package (and its network behavior) prior to giving credentials. - Note the mismatch: registry metadata said no env vars while clawhub.json and trader.py require SIMMER_API_KEY — ask the publisher to correct metadata or explain why the public summary omitted the credential requirement. - Run initially in paper/sim mode (default) and review logs and actual API calls. Only enable live trading after thorough code review and testing. - If you lack comfort reviewing Python packages or auditing API permissions, do not provide real API keys or enable live mode.

Like a lobster shell, security has layers — review code before you run it.

latestvk974jjqfdchfxqfw43bz855e1585299a
149downloads
0stars
3versions
Updated 1w ago
v0.0.2
MIT-0

Macro Asymmetric Longshot Trader

This is a template. The default signal scans for longshot markets (2-10% probability) and scores their macro support using cross-category related markets -- remix it with news sentiment analysis, social media signals, or expert forecaster aggregation. The skill handles all the plumbing (market discovery, category classification, macro scoring, trade execution, safeguards). Your agent provides the alpha.

Strategy Overview

Most prediction market participants avoid longshots entirely ("5% means it won't happen") or pick them randomly based on gut feeling ("wouldn't it be cool if..."). Neither approach is systematic.

This trader scans ALL markets for longshots priced between 2% and 10%, then uses CROSS-CATEGORY macro signals to identify which longshots are systematically underpriced. A $5 bet at 5% returns $100 if right. The edge isn't in predicting any single longshot correctly -- it's in finding the ones where the market is pricing 5% but the macro context suggests 15-30%.

Edge

Cross-category macro support scoring separates randomly cheap markets from systematically underpriced ones:

  1. Crypto ladder effect -- If "BTC above $60k" is at 80% and "BTC above $65k" is at 50%, then "BTC above $70k" at 6% is likely underpriced. The probability ladder should be smoother than what retail prices -- they dramatically underweight tail scenarios when the body of the distribution is already moving.

  2. Health escalation cascades -- If "measles > 500 cases" is at 85% and "measles > 1000" is at 60%, then "measles > 2000" at 5% is underpriced. Epidemics have exponential growth dynamics that make escalation more likely than linear extrapolation suggests.

  3. Geopolitical heating -- If multiple escalation markets (sanctions, troop movements, diplomatic breakdowns) are above 40%, then extreme outcome longshots (war, invasion, regime change) carry more probability than standalone analysis suggests. Geopolitical events cluster.

  4. Economic contagion -- If recession indicators, rate expectations, and trade war markets are all heating up, extreme economic longshots (sovereign default, currency crisis) have hidden support.

  5. Asymmetric payoff -- Even with a 20% hit rate on longshots that pay 10x, expected value is 2x. The strategy is profitable in aggregate, not on any single bet.

Signal Logic

  1. Discover ALL active markets via keyword search + get_markets(limit=200) fallback
  2. Filter for longshots: p between 0.02 and LONGSHOT_CEILING (default 0.10)
  3. Classify each longshot into a category (crypto, health, geopolitics, economic, political)
  4. Compute macro_support_score (0.0 to 1.0) by checking related markets:
    • Crypto: Check if lower threshold markets are likely (ladder analysis)
    • Health: Check if lower case-count markets are likely (escalation ladder)
    • Geopolitics: Check if related escalation markets are heating up
    • Economic: Check if related macro indicators are heating up
    • Political: Check if related political markets show instability
  5. Only trade longshots with macro_support >= MIN_SUPPORT (default 0.40)
  6. Size = max(MIN_TRADE, conviction * LONGSHOT_SIZE_CAP * MAX_POSITION)
  7. Sort by support score descending -- best-supported longshots first

How Macro Support Scoring Works

Crypto Ladder Example:

MarketPRole
BTC above $60k80%Lower threshold (support)
BTC above $65k50%Lower threshold (support)
BTC above $70k6%LONGSHOT -- avg lower = 65%, score = 0.78
BTC above $80k3%LONGSHOT -- avg lower = 45%, score = 0.54

Health Escalation Example:

MarketPRole
Measles > 50085%Lower threshold (support)
Measles > 100060%Lower threshold (support)
Measles > 20005%LONGSHOT -- avg lower = 72%, score = 0.94

Geopolitics Heating Example:

MarketPRole
New sanctions on X?65%Escalation signal
Troops deployed to Y?45%Escalation signal
Full-scale war in Z?4%LONGSHOT -- 2 signals avg 55%, score = 0.66

How Sizing Works

Position size is capped at LONGSHOT_SIZE_CAP (30%) of MAX_POSITION because longshots are inherently risky. With defaults (MIN_TRADE=$5, MAX_POSITION=$40, cap=30% -> max=$12):

pSupportConvictionSizePayoff if right
10% (ceiling)0.800%$5 (floor)$50
8%0.8016%$5 (floor)$63
5%0.8040%$5 (floor)$100
3%0.9063%$8$267
2%1.0080%$10$500

Keywords Monitored

bitcoin above, btc above, ethereum above, eth above,
solana above, sol above, xrp above, crypto price,
measles, bird flu, avian flu, pandemic, outbreak,
war, invasion, escalation, sanctions, nuclear,
tariff, trade war, embargo, coup, resign,
impeach, default, recession, rate cut, rate hike

Remix Signal Ideas

  • News sentiment NLP: Score longshot markets against recent news headlines -- a sudden spike in news mentions of a topic dramatically increases the probability of related longshots
  • Expert forecaster aggregation: Cross-reference Polymarket longshot prices with Metaculus, Good Judgment Open, or Manifold Markets -- if experts price the event at 15% but Polymarket prices it at 5%, strong support signal
  • Historical base rates: For recurring events (annual measles counts, quarterly GDP, monthly employment), check the historical frequency of extreme outcomes -- longshots on events that happen 15% of the time historically but are priced at 5% are systematically underpriced
  • Social media spike detection: Track Twitter/Reddit mention velocity for longshot topics -- viral attention often precedes probability repricing by 12-48 hours

Safety & Execution Mode

The skill defaults to paper trading (venue="sim"). Real trades only with --live flag.

ScenarioModeFinancial risk
python trader.pyPaper (sim)None
Cron / automatonPaper (sim)None
python trader.py --liveLive (polymarket)Real USDC

autostart: false and cron: null -- nothing runs automatically until you configure it in Simmer UI.

Required Credentials

VariableRequiredNotes
SIMMER_API_KEYYesTrading authority. Treat as high-value credential.

Tunables (Risk Parameters)

All declared as tunables in clawhub.json and adjustable from the Simmer UI.

VariableDefaultPurpose
SIMMER_MAX_POSITION40Max USDC per trade (reached at 100% conviction)
SIMMER_MIN_TRADE5Floor for any trade (min USDC regardless of conviction)
SIMMER_MIN_VOLUME3000Min market volume filter (USD)
SIMMER_MAX_SPREAD0.10Max bid-ask spread (10% -- wider for thin longshot markets)
SIMMER_MIN_DAYS1Min days until resolution
SIMMER_MAX_POSITIONS10Max concurrent open positions
SIMMER_YES_THRESHOLD0.38Standard YES threshold (used for non-longshot fallback)
SIMMER_NO_THRESHOLD0.62Standard NO threshold (used for non-longshot fallback)
SIMMER_LONGSHOT_CEILING0.10Max probability to qualify as a longshot (10%)
SIMMER_MIN_SUPPORT0.40Min macro support score to trade a longshot
SIMMER_LONGSHOT_SIZE_CAP0.30Max fraction of MAX_POSITION for longshot sizing (30%)

Dependency

simmer-sdk by Simmer Markets (SpartanLabsXyz)

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